Systems and methods for detection of particles in a beneficial agent

ABSTRACT

Detection of particles in a liquid beneficial agent contained within a container includes selectively illuminating at least a portion of the liquid beneficial, obtaining an image from the illuminated portion of the liquid beneficial agent, analyzing image data representing the image, using a data processor, to obtain a particle concentration, measuring an image intensity value of the image data using the data processor, and determining a quality level of the liquid beneficial agent using the data processor based on the particle concentration and the measured image intensity value.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application claims the benefit of U.S. Provisional Application No.61/651,211, filed May 24, 2012, which is incorporated by referenceherein in its entirety.

BACKGROUND

1. Field of the Disclosed Subject Matter

The present disclosed subject matter relates to systems and methods fordetection of particles, such as protein monomers, protein aggregates andforeign particles, which can be found in a liquid beneficial agent.

2. Description of Related Art

Beneficial agents for diagnostic and therapeutic uses typically areavailable in liquid form. Such liquid beneficial agents can bebiologics, small molecule pharmaceuticals, nutritional products, orcombinations thereof. It is often helpful, if not necessary, to inspectsuch liquid beneficial agents to ensure particles, contaminants,aggregates, or other undesirable materials are not present. Preferably,such inspection occurs during manufacture and packaging. Additionally,however, such inspections may be helpful after shipping, during storage,and/or prior to use.

One of the most common routes of administration for liquid beneficialagents is by injection, including intravenous, subcutaneous orintramuscular injection. For example, a syringe containing the liquidbeneficial agent can be used for the injection, which typically iscarried out by medical personnel or other health care providers. Incertain instances, a patient is trained in the use of the syringe toallow for self-injection. Moreover, certain medications are formulatedin pre-filled syringes for patient use, to avoid the need for thepatient to fill the syringe. Such pre-filled syringes can be packaged inan automatic injection device, which provides an easier-to-use and morerapid delivery system for the beneficial agent.

As noted, it can be helpful or necessary to inspect the contents of thepre-filled syringe to ensure quality and safety of the beneficial agent.For example, it is often desirable to inspect biological drugs forprotein aggregates. When biological drugs are formulated at relativelyhigh concentrations or volumes, the risk of generating molecularaggregates can increase. These aggregates can range in size from a fewnanometers to many microns.

Naked eye inspection of the contents of a syringe is a recognized andgenerally acceptable method used for quality control. However, naked eyeinspection can be subjective and can lack the sensitivity to detect lowconcentrations of particles or subvisible particles. Certain commercialsystems have been developed with automated operation and relatively highsample throughput inspection of syringe contents for particles. Somecommercially available systems, for example Seidenader VI series andBrevetti K15 systems, can provide high-throughput syringe inspectionnoninvasively, but can only effectively detect “visibles” (i.e.,particles larger than about 10-25 microns). In contrast, some knownexperimental research lab systems can provide higher resolution particledetection, but these systems rely on manual and/or invasive techniquesthat render relatively low sample throughput. For example, dynamic lightscattering (DLS) can provide a molecular resolution of about 1 nm, andNanoparticle Tracking Analysis (NTA), used in systems marketed byNanoSight Ltd., can image particles as small as about 20 nm. However,these invasive techniques have a relatively low throughput compared toother methods.

U.S. Patent Application Publication No. 2010/0102247 to Arvintedescribes a digital scanner-based particle detection technique forimproved sensitivity over commercial systems. However, such a system canbe limited by the resolution of the scanner and relatively low contrast,and thus can be ineffective at detecting low concentrations ofsubvisible particles (for example, below about 1 to 10 microns in size).

As such, there remains a need for systems and methods that cannoninvasively provide high-throughput, high-sensitivity evaluation ofliquid beneficial agents, particularly in pre-filled syringes, to detectthe presence of sub-micron particles, even in low concentrations.

SUMMARY

The purpose and advantages of the disclosed subject matter will be setforth in and apparent from the description that follows, as well as willbe learned by practice of the disclosed subject matter. Additionaladvantages of the disclosed subject matter will be realized and attainedby the methods and systems particularly pointed out in the writtendescription and claims hereof, as well as from the appended drawings.

To achieve these and other advantages and in accordance with the purposeof the disclosed subject matter, as embodied and broadly described, thedisclosed subject matter includes a method for detection of particles ina liquid beneficial agent contained within a container. The methodincludes selectively illuminating at least a portion of the liquidbeneficial agent; obtaining an image from the illuminated portion of theliquid beneficial agent; analyzing image data representing the image,using a data processor, to obtain a particle concentration; measuring animage intensity value of the image data using the data processor; anddetermining a quality level of the liquid beneficial agent using thedata processor based on the particle concentration and the measuredimage intensity value.

For example and as embodied herein, selectively illuminating a portionof the liquid beneficial agent can include focusing light through anoptical element corresponding to the container to provide an undistortedimage from the illuminated portion of liquid beneficial agent.Selectively illuminating the portion of the liquid beneficial agent canalso include forming a thin sheet of illumination in the illuminatedportion of the liquid beneficial agent. The liquid beneficial agent canbe selectively illuminated with light having a wavelength in a rangefrom about 200 nm to about 1100 nm.

In some embodiments, the image is obtained by or as a result of lightscattering from the particles in the illuminated portion of thebeneficial agent. Additionally or alternatively, the liquid beneficialagent can have intrinsic fluorescence, and the liquid beneficial agentcan be selectively illuminated with light having an excitationwavelength suitable to cause the liquid beneficial agent to emitfluorescent light of an emission wavelength. Obtaining the imagetherefore can include using an optical filter corresponding to theemission wavelength of the emitted fluorescent light. Obtaining theimage can also include focusing an image detector through an opticalelement corresponding to the container to provide an undistorted imagefrom the liquid beneficial agent. Additionally or alternatively,obtaining the image can include the use of a difference image analysistechnique, wherein a first image and a second image are captured fromthe illuminated portion of the liquid beneficial image, and then adifference image can be obtained from the first image and the secondimage to correct for interfering background.

Furthermore and as embodied herein, the method can include calibratingan image detector to a predetermined sensitivity. Analyzing the imagedata to obtain a particle concentration thus can be performed using asingle image frame and include counting a number of particles exceedinga size threshold or an intensity threshold to determine a particleconcentration and analyzing a particle intensity distribution. Bycontrast, measuring the image intensity value of the image data caninclude determining a pixel intensity value of each pixel of a pluralityof pixels of the image data using the data processor and combining thepixel intensity values of the plurality of pixels to determine the imageintensity value using the data processor. Determining the quality of theliquid beneficial agent thus can include comparing the particleconcentration to a particle concentration threshold, as well ascomparing the image intensity value to an image intensity threshold. Theparticle concentration threshold and the image intensity threshold canbe obtained from a representative profile. The method can also includedetermining an average molecular mass of the particles using the imageintensity value, wherein the quality level is further determined usingthe average molecular mass. The detection therefore can be performed ona plurality of containers in a high-throughput manner.

The disclosed subject matter also includes a system for detection ofparticles in a liquid beneficial agent within a container. The systemincludes a light source configured to illuminate at least a portion ofthe liquid beneficial agent, an image detector configured to obtain animage from the illuminated portion of the liquid beneficial agent, and adata processor coupled to the image detector. The data processor isprogrammed to analyze image data representing the image from the imagedetector to obtain a particle concentration; measure an image intensityvalue of the image data; and determine a quality level of the liquidbeneficial agent based on the particle concentration threshold and themeasured image intensity value. The system can include any or all of thefeatures described herein.

The disclosed subject matter also includes a beneficial treatmentproduct. The beneficial treatment product includes a containercontaining a liquid beneficial agent and a system for detection ofparticles in the liquid beneficial agent including any of the featuresdescribed herein.

The disclosed subject matter also includes a liquid beneficial agenthaving a predetermined quality level, as determined by the method fordetection described herein. For example, the liquid beneficial agent caninclude a protein. Particularly, the protein can be a fusion protein,and the liquid beneficial agent and can have a protein concentrationbetween about 0.1 mg/ml and about 200 mg/ml. The protein can be anantibody, and the antibody can be an anti-Tumor Necrosis Factor alpha(TNFα) antibody, or antigen-binding fragment thereof.

It is to be understood that both the foregoing general description andthe following detailed description are exemplary and are intended toprovide further explanation of the disclosed subject matter claimed.

The accompanying drawings, which are incorporated in and constitute partof this specification, are included to illustrate and provide a furtherunderstanding of the disclosed subject matter. Together with thedescription, the drawings serve to explain the principles of thedisclosed subject matter.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a diagram illustrating a representative method implementedaccording to an illustrative embodiment of the disclosed subject matter.

FIGS. 2A-2B are exemplary images illustrating the result of using anoptical element to obtain an image in accordance with the disclosedsubject matter.

FIGS. 3A-3D are exemplary images illustrating the result of usingdifference image analysis to obtain an image in accordance with thedisclosed subject matter.

FIGS. 4A-4C are exemplary images illustrating the result of directimaging in accordance with the disclosed subject matter.

FIGS. 5A-5D are exemplary images illustrating evaluating a sample byparticle counting in accordance with the disclosed subject matter.

FIGS. 6A-6D are exemplary images illustrating the result of indirectimaging in accordance with the disclosed subject matter.

FIG. 7 is an exemplary graph illustrating determining an image intensityin accordance with the disclosed subject matter.

FIG. 8 is an exemplary graph illustrating the relationship between imageintensity and concentration in accordance with the disclosed subjectmatter.

FIGS. 9A-9B are exemplary images illustrating the result of indirectimaging on an untreated sample and a heat-treated sample, respectively,for purpose of comparison.

FIG. 10 is an exemplary graph illustrating the image intensity of thesamples of FIGS. 9A-9B, for purpose of comparison.

FIG. 11 is a representative graph of the samples of FIGS. 9A-9B obtainedusing a dynamic light scattering technique for purpose of comparison.

FIG. 12 is an exemplary diagram illustrating exemplary results ofindirect imaging analysis on multiple samples for purpose of comparison.

FIG. 13 is a diagram illustrating a representative system for use withthe method of FIG. 1 according to an illustrative embodiment of thedisclosed subject matter.

FIG. 14 is an exemplary diagram illustrating further details of a systemfor use with the method of FIG. 1.

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENT

Reference will now be made in detail to the various exemplaryembodiments of the disclosed subject matter, exemplary embodiments ofwhich are illustrated in the accompanying drawings. The structure andcorresponding method of operation of the disclosed subject matter willbe described in conjunction with the detailed description of the system.

The systems and methods presented herein can be used for detection ofparticles, such as proteins and protein aggregates or any other visibleor subvisible particles, in any of a variety of suitable beneficialagents or substances. As used herein, a “liquid beneficial agent” or“beneficial agent” (used interchangeably herein) is intended to refergenerally to a substance or formulation in liquid form to beadministered to or used by an individual (also referred to herein as auser or a patient) for an approved medical indication, such as amedication, diagnostic, nutritional, or other therapeutic agent.

In accordance with the disclosed subject matter herein, a method fordetection of particles in a liquid beneficial agent contained within acontainer (also referred to herein as a “detection method”) generallyincludes selectively illuminating at least a portion of the liquidbeneficial agent; obtaining an image from the illuminated portion of theliquid beneficial agent; analyzing image data representing the image,using a data processor, to obtain a particle concentration; measuring animage intensity value of the image data using the data processor; anddetermining a quality level of the liquid beneficial agent using theparticle concentration and the measured image intensity value.

The accompanying figures, where like reference numerals refer toidentical or functionally similar elements throughout the separateviews, further illustrate various embodiments and explain variousprinciples and advantages all in accordance with the disclosed subjectmatter. For purpose of explanation and illustration, and not limitation,exemplary embodiments of systems and methods for detecting particles ina beneficial agent in accordance with the disclosed subject matter areshown in FIGS. 1-14. While the present disclosed subject matter isdescribed with respect to using the systems and methods to detectaggregated proteins in a liquid beneficial agent, for example a TNFinhibitor, one skilled in the art will recognize that the disclosedsubject matter is not limited to the illustrative embodiment. Forexample, the detection method can be used to detect any suitableparticles, either visible or subvisible, in a liquid beneficial agent,such as contaminants or other undesired particles. In addition, thecomponents and the method of detecting particles in a liquid beneficialagent are not limited to the illustrative embodiments described ordepicted herein.

FIG. 1 is a diagram showing an exemplary method according to thedisclosed subject matter. At 100, the device and beneficial agentcontainer are made ready for analysis. Certain additional steps, such ascalibrating an image detector to a desired sensitivity, can be performedinitially and/or periodically, and repeated when each new type ofbeneficial agent is to be evaluated. Additional adjustments to thesystem can include the position of the image detector, the position orconfiguration of optical elements, the wavelength, intensity, orposition of the light source, or other applicable parameters describedherein. By contrast, some steps can be performed for each beneficialagent container to be tested, such as physically placing the beneficialagent container into alignment with a light source and an imagedetector. When the steps to prepare the device and beneficial agentcontainer for analysis are completed, a signal can be provided to thedevice or to the user to indicate that the system is ready for testing.

At 102 of FIG. 1, at least a portion of the beneficial agent in thecontainer is selectively illuminated. If desired, the entire contents ofthe container can be analyzed. Illuminating the beneficial agent caninclude directing a light source at the portion of the beneficial agentto be analyzed.

In accordance with one aspect of the disclosed subject matter, thebeneficial agent is illuminated by a thin sheet of illumination. Thethin sheet of illumination can be formed by the light source, or by anoptical element. Forming a thin sheet of illumination in the beneficialagent can create a substantially planar field of light observable by animage detector, and can enhance contrast of an image obtained of thebeneficial agent in the area of the thin sheet of illumination. Enhancedcontrast of the image can allow for imaging of particles of submicrondimensions, including detecting particles much smaller than thewavelength of light, using the image analysis techniques describedbelow. In some embodiments, selectively illuminating the beneficialagent can include focusing light through an optical elementcorresponding to the container. That is, an optical element, such as acylindrical lens, can be provided between the light source and thesyringe to form the thin sheet of illumination, as well as operate inconcert with the syringe and the image detector to eliminate distortioncaused by the curvature of the syringe wall. For example, the beneficialagent container can have a curvature that distorts the focus of thelight through the container. An optical element, such as a lens, havinga curvature corresponding to the curvature of the container can beintroduced between the light source and the container to offset thecurvature of the container and better focus the light through thecontainer.

The light source can be any suitable light source to illuminate thecontainer. For example and without limitation, the light source can be acoherent light source, such as a laser. The light source can be selectedto produce light having a particular wavelength. For example and withoutlimitation, the light source can provide light having a wavelengthselected from a range of about 200 nm to about 1100 nm for a biologicproduct Light having a wavelength of about 200 nm to about 400 nm can besuitable for exciting an intrinsic fluorescence of a beneficial agent,as described further below. Light having a wavelength of about 400 nm toabout 1100 nm can be suitable to allow for light scattering by theparticles, which can then be imaged as described further below.

At 104 of FIG. 1, an image from the illuminated portion of the liquidbeneficial agent is obtained. The image obtained can be due to lightscattering from particles in the illuminated portion of the beneficialagent. Obtaining an image can include sending a signal to the imagedetector to capture the image. In some cases, such as if a new type ofbeneficial agent and/or container is being tested or if theconfiguration of the detection system has been changed, the imagedetector can first be calibrated to a predetermined sensitivity and/orwith a baseline product of a known quality level. In some embodiments,obtaining an image can include focusing the image at the image detectorthrough an optical element corresponding to the container. For example,the beneficial agent container can have a curvature that distorts thefocus of the image detector through the container. Hence, and aspreviously noted, an optical element, such as a lens, having a curvaturecorresponding to the curvature of the container can be introducedbetween the image detector and the container to offset the curvature ofthe container and provide an image that is substantially free ofdistortion from the curvature of the container. Further, an opticalelement, such as a microscope objective lens, optically coupled with theimage detector can be used to obtain an image of the beneficial agentwith increased resolution. Increased resolution of the image can allowdetection of particles in the beneficial agent using the image analysistechniques further described below.

FIGS. 2A and 2B are exemplary images from a beneficial agent obtained byan exemplary image detector 204. FIG. 2A shows an image obtained from abeneficial agent in a pre-filled syringe container 206 without the useof optical elements 208. FIG. 2B shows an image obtained from abeneficial agent in a pre-filled syringe container 206 with the use ofoptical elements 208, the image being relatively free of distortioncompared to the image of FIG. 2A.

For example and without limitation, reference is made to performing thedetection method by obtaining a single, still-frame image of the liquidbeneficial agent. However, it will be understood that the detectionmethod can be performed by taking a series of still-frame images, amotion video image or photodetector signal of the liquid beneficialagent over a period of time if dynamic analysis is desired.Additionally, while the detection method can be performed using an imageof only a select portion of the liquid beneficial agent, the method canlikewise be applied to or across the entire contents of the pre-filledsyringe container 206. For example, the pre-filled syringe container 206can be translated across a fixed light in multiple steps to obtainmultiple images of the liquid beneficial agent, and/or the light fromthe light source can be redirected across selected portions of thecontainer to obtain corresponding images. However, reducing the numberof image frames obtained and/or reducing the size of the portion of thecontainer to be imaged can increase the throughput, i.e., the number ofcontainers that can be tested in a given time. Hence, high-throughputdetection can be performed by utilizing a single frame image of only aportion of the liquid beneficial agent.

Additionally or alternatively, an image from the beneficial agent can beobtained by utilizing an intrinsic fluorescence of the beneficial agent.In certain beneficial agents, for example biologic protein drugs,excitation of intrinsic protein fluorescence due to natural, unmodifiedamino acids in the beneficial agent can be achieved by illumination ofthe beneficial agent with light having a wavelength within an absorptionband. For example, a wavelength within an absorption band can be withina range of about 200 nm to about 330 nm for certain TNF inhibitors.Excitation of the beneficial agent can cause the beneficial agent toemit fluorescence having an emission wavelength, for example, within arange of about 290 nm to about 500 nm. Other beneficial agents, such assmall molecule drugs that are intrinsically fluorescent, can be excitedat substantially any suitable ultraviolet, visible, or near-infraredwavelength (for example from about 200 nm to about 900 nm). Hence, animage from the beneficial agent can be obtained by placing an opticalfilter having a wavelength band corresponding to the emission wavelengthof the beneficial agent within the view of the image detector.

Utilizing the intrinsic fluorescence of the beneficial agent to obtainan image can also be incorporated into the system according to thedisclosed subject matter to provide calibration and troubleshootingfunctionality. For example, in addition or as an alternative to thesteps described with respect to 100 of FIG. 1, the image of thebeneficial agent obtained utilizing the intrinsic fluorescence of thebeneficial agent can be obtained initially and/or periodically, or wheneach new type of beneficial agent is to be evaluated. The image can beanalyzed to determine if particles being imaged are indeedprotein-containing particles, and not, for example, contaminateparticulates, oil droplets, air bubbles, or other undesired non-proteinparticles. Such undesired particles can be imaged using lightscattering, but would not appear in an image obtained utilizingintrinsic fluorescence. If such particles do appear during lightscattering, certain parameters of the system can be adjusted, such asthe sensitivity or position of the image detector, the position orconfiguration of the optical elements, the wavelength, intensity, orposition of the light source, or any other parameters described herein.Once the system is calibrated utilizing intrinsic fluorescence toconfirm that the particles being imaged using light scattering areproteins, detection using light scattering can proceed.

Additionally or alternatively, an image from the beneficial agent can beobtained, using a difference image analysis technique, wherein adifference image can be obtained between two images of the beneficialagent. For example, images of certain samples can have a strong Rayleighscattering background, which can be caused by a relatively high proteinconcentration. As such, these images can have a relatively lowsignal-to-background ratio that can be unsuitable for quantitativedetection of particles or aggregates present at low concentrations. Thelight scattered from concentrated protein monomers can be considered asa steady background image. Accordingly, determining a difference image(or “difference image analysis”) can reduce the interfering backgroundto provide an image suitable for quantitative detection of particles oraggregates.

As embodied herein, for purpose of understanding and not limitation, toperform difference image analysis, a first image and a second image ofthe illuminated portion of the sample can be taken successively. FIG. 3Aillustrates an example first image, and FIG. 3B illustrates an examplesecond image. Due at least in part to the movement or diffusion ofparticles within the sample, particles can appear in different positionsin the second image compared to the first image. As such, a differenceimage can be calculated, for example using ImageJ software availablefrom the National Institutes of Health (NIH), or similar software, todetermine a difference between the first image and the second image, andthus reduce the background interference present in the first and secondimages. An exemplary difference image obtained from the first image andsecond image is illustrated in FIG. 3C. As shown in FIG. 3C, backgroundinterference is reduced, and a number of particles are visible. Theblack and white contrast of the difference image can be increased toimprove the visibility of the particles, as shown for example in FIG.3D. As such, and as depicted for purpose of illustration herein,performing particle counting on the image of FIG. 3D, as discussedfurther herein, determines a total of 7 particles in the exemplarydifference image, which corresponds to 3.5 particles per image. Usingthe difference image, the image processing techniques described furtherherein can be performed, as described further below.

At 106 of FIG. 1, the image obtained at 104 is processed to determinecertain characteristics of the image, from which characteristics of theliquid beneficial agent under investigation can be determined. Inaccordance with the disclosed subject matter, and as embodied herein,two or more image processing techniques are performed independently orin combination on the single image. Combining the two or more imageprocessing techniques thus increases the range and accuracy of particlesizes that can be detected using the detection method. For example andwithout limitation, and as embodied herein, particles of about 25 nm orgreater can be directly identified in the image, and one skilled in theart will recognize that other sizes of particles can be imaged based atleast in part on the optical conditions of the system and/or the type ofsample being imaged.

The direct imaging technique, such as nanoparticle imaging or othersuitable technique, can be performed on the image of the beneficialagent. Direct imaging can be used to obtain a particle concentration.For example and without limitation, the image can be evaluated bycounting a number of particles exceeding a size threshold or anintensity threshold to determine a particle concentration. Counting thenumber of particles exceeding the size threshold or the intensitythreshold can be performed using a number of known techniques. Forexample, particle scattering intensities can be used to estimateparticle mass. A particle intensity distribution thus can be generatedby identifying the number of particles exceeding a certain predeterminedparticle scattering intensity and plotting the number of particles overthe corresponding image area to obtain a particle concentration.Alternatively, if the number of particles that exceed a predeterminedsize or intensity is known, then plotting is not required. A variety ofsuitable algorithms for direct imaging can be used to analyze an imageand obtain the particle concentration. For example and withoutlimitation, currently-available software, such as ImageJ, can beutilized to perform these functions. Various tools available throughImageJ, such as “Maximum,” “Analyze Particle,” and “Histogram,” or othersuitable software tools can be used to perform particle identification,particle counting, measuring image intensity distributions or the like.Additional tools and software likewise can be used and/or be adaptedaccording to the intended implementation. Accordingly, as will bediscussed below, whether and how many particles identified in the imageexceed the particle concentration can be used as a factor to determinethe quality of the beneficial agent.

For purpose of illustration and not limitation, FIGS. 4A-4C areexemplary images obtained from a representative image detector of asystem according to the disclosed subject matter. FIG. 4A shows an imageobtained of 80 nm particles suspended in water. FIG. 4B shows 290 nmparticles suspended in water. FIG. 4C shows an image obtained of 500 nmparticles suspended in water. The images were obtained under similarconditions of illumination and detection sensitivity. Thus, FIGS. 4A-4Cillustrate the performance of the system with respect to direct imagingof sub-micron particles. FIGS. 4A-4C can be analyzed, as describedabove, by the direct imaging technique to obtain a particleconcentration, for example by counting a number of particles exceeding asize threshold or an intensity threshold.

Furthermore, for a sample considered to have a spatially uniformconcentration, the particle concentration (i.e., the number of particlesper unit volume) can be deduced from an analysis of the number ofparticles from the measured region of the solution, as described herein.The particle number in one image can thus be considered to be equal tothe particle number in the detection volume, and the detection volumecan be estimated from the illumination volume. For example, if anillumination area shown in the image is 2 mm by 2 mm, and the thicknessof the beam is 0.1 mm, the illumination volume can be determined to be0.4 microliters. As an additional and confirmatory technique ofcalibration, a standard solution with known particle concentration canbe used, for example and as embodied herein, 490 nm polystyreneparticles in water. Alternatively, for solutions that are not consideredto be spatially uniform (i.e. spatially non-uniform concentration), itcan be beneficial or even necessary to scan the entire solution.

The total particle number in a container (N_(total)) can be determinedby the relation,

$\begin{matrix}{{N_{total} = \frac{N_{{per}\_ {image}}V_{total}}{V_{detection}}},} & (1)\end{matrix}$

where N_(per) _(—) _(image) represents the total number of particles inthe image, V_(total) represents the total volume of the container andV_(detection) represents the volume imaged in a single image.

For purpose of illustration and understanding, FIGS. 5A-5D are exemplaryimages illustrating evaluating a sample by determining a particleconcentration or “particle counting” according to the disclosed subjectmatter. FIG. 5A shows an image obtained of a sample containing 25 mg/mlof bovine serum albumin (BSA) prepared from a powder and without anyfiltration. FIG. 5C shows an image obtained of a sample containing 25mg/ml of BSA that was filtered with a 0.2 micron filter. Theillumination volume for each image was determined to be 0.25 microliters(0.00025 mL), as described above. Particle counting was performed usingImageJ on each of the images of FIGS. 5A and 5C to determine a particleconcentration. FIG. 5B illustrates the result of the particle countingof the image of FIG. 5A. As shown in FIG. 5B, 1023 particles weredetected in the image, which corresponds to a particle concentration ofabout 4.1 million particles per mL (1023 particles/0.00025 mL=4.092million particles/mL). By comparison, as shown in FIG. 5D, 4 particleswere detected in the image of FIG. 5B, which corresponds to a particleconcentration of about 16,000 particles per mL (4 particles/0.00025mL=16,000 particles/mL).

A user can establish a threshold of particle concentration based on adesired quality of a particular sample to be measured. A sample having aparticle concentration exceeding the threshold can be determined to be“unacceptable,” and thus no further testing of the unacceptable sampleneed be performed. A sample having a particle concentration that doesnot exceed the threshold can be subjected to further analysis bydetermining a total image intensity, from which an average molecularweight can be determined, as described herein. As such, the presence ofvery small aggregates or particles (for example and as embodied herein,less than about 100 nm), which can be too small to be imaged as discreteparticles and thus too small to be counted by particle counting, canstill be detected by the subsequent technique.

Separately, a total image intensity analysis can be performed todetermine a total image intensity, from which an average molecular massof particles in the beneficial agent can be determined. The total imageintensity analysis can be based on static light scattering (SLS), whichcan be considered as an indirect imaging technique, and can allow fordetection of particles as small as about 10 nm or less. SLS-basedindirect imaging can include measuring an image intensity value of theimage data. The total image intensity value can be measured, forexample, by determining or obtaining a pixel intensity value of eachpixel representing the image, or a region of the image of interest, andcombining the pixel intensity values obtained to determine the totalimage intensity value. The total image intensity value can be divided bythe number of pixels to obtain an average image intensity value for theimage. A variety of suitable algorithms can be used to measure an imageintensity value from image data. For example and without limitation,currently-available software, such as ImageJ by the National Institutesof Health described above, can be used to perform these functions. Theimage intensity value can be considered to be proportional to theaverage molecular mass and particle concentration of the particles,including molecules, in the measured region, offset by a backgroundintensity.

For purpose of illustration and understanding, FIGS. 6A-6D are exemplaryimages obtained from a representative image detector of a systemaccording to the disclosed subject matter. FIG. 6A shows an imageobtained of Milli-Q water in a syringe, which can be representative of abackground intensity. FIGS. 6B-6D each shows an image of BSA in asyringe at different concentrations, i.e., 12.5 mg/mL, 25 mg/mL and 50mg/mL, respectively.

FIGS. 6A-6D illustrate the performance of the system with respect toindirect imaging of particles that are too small to be detected usingdirect imaging. In FIGS. 6B-6D, for purpose of illustration, anegligible number of particles are observable since any BSA monomers andlow molecular weight aggregates, which represent substantially the massof the sample, are too small to be imaged directly. However, and unlikea conventional system, the system disclosed herein can detect thepresence of the BSA since the SLS-intensity (i.e., the total imageintensity or the average image intensity) exceeds the backgroundintensity of FIG. 6A.

Furthermore, the total image intensity can be determined by measuring anintensity of each pixel in an image, for example by using ImageJ orsimilar software. The intensity of each pixel can be represented in ahistogram. For example, FIG. 7 is a histogram illustrating the intensityof each pixel of the sample of FIG. 6D having 50 mg/mL BSA. The totalimage intensity can be determined, for example, by integrating (i.e.,finding the area under) the plot of the intensity of each pixel in FIG.7. For example, as shown in FIG. 7, the total image intensity (or “totalintegrated intensity”) is determined to be 2.17×10⁷.

Based upon the above, the image intensity value and particleconcentration can be used to determine an average molecular weight ofthe particles in the sample, and as such can be used as a factor todetermine the quality of the beneficial agent. For example, and forpurpose of understanding and not limitation, under Rayleigh scatteringconditions, the image intensity value (I_(Total)) can be consideredlinearly proportional to the average molecular weight (M_(W)) andconcentration (C), offset by a background intensity (I_(background)), asrepresented by,

I _(Total) =B _(constant) M _(w) C+I _(background).  (2)

As such, with a sample including a protein of known molecular weight andindependently determined concentration, the instrument constant(B_(constant)) can be determined, and the system can be calibrated foraverage molecular weight detection using eq. (2) above. The backgroundintensity can be measured with a baseline solution, for example asolution of pure water or buffer without protein. Further details ofstatic light scattering techniques to characterize molecules, andrelated aspects of physical chemistry as known in the art, can be reliedupon for further understanding and modification of the disclosed subjectmatter.

FIG. 8 is a diagram illustrating the total image intensity of eachsample having different concentrations of BSA. As shown in FIG. 8, forpurpose of illustration and not limitation, the total image intensityhas a linear relationship to particle concentration. FIG. 8 illustratesthat the technique according to the disclosed subject matter canquantitatively detect variations in concentration of a moderately sizedprotein (i.e., BSA having a molecular weight of about 67 kD) down toless than 5 mg/mL. As such, the technique according to the disclosedsubject matter can be applied to biologic beneficial agents, which cantypically have a molecular weight of about 150 kD, even at lowconcentrations.

To further illustrate the effectiveness of the system disclosed herein,without limitation, a sample having a 12.5 mg/mL concentration of BSA,was heated to 65° C. for one minute to cause some degree of denaturationand aggregation. FIGS. 9A-9B illustrate images of the sample of theuntreated sample (FIG. 9A) and the heat-treated sample (FIG. 9B),respectively, for purpose of comparison. Comparing the samples of FIGS.9A-9B, naked eye inspection of the syringes did not show an apparentdifference between the samples. Furthermore, particle counting did notmeasure a detectable difference in aggregates caused by heating thesample. However, by obtaining the average image intensity value usingthe SLS-based measuring technique, even in the absence of resolvableparticles, the diffuse white sheen across the image in FIG. 9B yields atotal image intensity of about 3.1×10⁷. FIG. 10 illustrates the totalimage intensity of the untreated sample of FIG. 9A compared to theheat-treated sample of FIG. 9B. The heat-treated sample was measured tohave approximately a 5.6-fold increase in total image intensity over theuntreated sample of FIG. 9A, after subtracting the background scatteringobtained from FIG. 6A. Based on an average molecular weight of untreatedBSA of 72.6 kD (assuming a 10% dimer content of a typical commercialproduct), the result illustrates that the average molecular weight ofthe heat-treated sample has increased to 403.7 kD. Thus, the degree ofdenaturation and/or aggregation caused by heating sample FIG. 9A can beshown.

To further demonstrate the benefit of the methods and systems disclosedherein, and merely for purpose of comparison, FIG. 11 is a diagramillustrating a mass-weighted molecular size distribution obtained by anoffline DLS-based analysis of the same samples imaged in FIGS. 9A and9B. FIG. 11 illustrates that the heat treatment caused an increase insmall-sized aggregates (i.e., less than 35 nm for this sample).

Furthermore, it is noted for purpose of explanation that the intrinsicmolecular particle size distribution of the BSA solution of FIG. 9A isslightly heterogeneous, and thus the mass-weighted particle sizedistribution shown in FIG. 11 is centered around 7 nm diameter, withslight broadness. After the heat treatment of the sample resulting inthe FIG. 9B image, DLS analysis ascertains a significantly perturbedsample consisting of the native monomer (at about 7 nm) plus smalleraggregates. As such, the bulk of these smaller aggregates are too smallto be detected as distinct “particles” in the direct imaging mode, butcan be detected by the SLS-based indirect imaging analysis of thedisclosed method and system.

With reference to FIG. 12, a diagram is provided showing exemplaryresults of SLS-based indirect imaging analysis performed on images of 20different pre-filled syringes. The vertical axis represents static lightscattering total intensity values measured by summing the intensities ofall pixels of each image. Sample 1 shows a total intensity value for animage from a syringe filled with water. Samples 2-12 show a totalintensity value for images from syringes containing a fresh beneficialagent of known and acceptable quality level. Such data can be used forpurpose of calibration of the system for determination of acceptablequality level, as described further below. Samples 13-15 show intensityvalues for images from syringes containing beneficial agents of extendedshelf-life but determined to be within acceptable quality level basedupon the method and system herein. Samples 16-20 show intensity valuesfor images of beneficial agents of extended shelf life but determined tohave an unacceptable amount of aggregated proteins.

At 108 of FIG. 1, the results of the two or more image processingtechniques performed in 106 are evaluated to determine a quality levelof the liquid beneficial agent. The determination of the quality levelcan be based independently on each of the results obtained by the imageprocessing techniques performed in 106. For example, the particleconcentration obtained from the direct imaging technique can be comparedto a particle concentration threshold. If the particle concentrationexceeds the particle concentration threshold, the quality of the liquidbeneficial agent can be considered to be unacceptable, and a warning canbe generated that the liquid beneficial agent has failed the inspection(at 110).

Separately, the image intensity value (total or average) measured usingthe indirect imaging technique can be compared to an image intensitythreshold. If the image intensity value exceeds the image intensitythreshold, then the quality of the liquid beneficial agent can beconsidered to be unacceptable, and a warning can be generated that theliquid beneficial agent has failed the inspection (at 110).Alternatively, the average molecular mass can be calculated from theimage intensity value, and the average molecular mass can be compared toan average molecular mass threshold to determine the quality of theliquid beneficial agent.

The method and system disclosed herein therefore can be used to confirmand/or determine acceptable quality levels of a beneficial agent inindividual containers at a high-throughput rate. For example, if all theresults of the image processing are evaluated and none of the resultsexceed predetermined threshold values, then the beneficial agent can beconsidered to be acceptable. An indication can be generated that theliquid beneficial agent has passed the inspection (at 112) and/or a newbeneficial agent can be made ready for inspection using the detectionmethod.

Alternatively, or additionally, and in accordance with another aspect ofthe disclosed subject matter, the quality level can be a function of theresults of the image processing techniques in combination. Arepresentative profile can relate the results obtained by the imageprocessing techniques to the quality level of the beneficial agent. Therepresentative profile embodied herein can contain the particleconcentration threshold and the total intensity threshold that, ifexceeded, indicate that the beneficial agent is unacceptable and doesnot pass inspection. The representative profile, and thus the particleconcentration threshold and the total intensity threshold, can be basedon a variety of factors, including but not limited to the type ofbeneficial agent being inspected, the concentration of the beneficialagent being inspected, and the optical configuration of the detectionsystem.

In accordance with another aspect of the disclosed subject matter, asystem is provided for detection of particles in a liquid beneficialagent contained within a container (also referred to herein as a“detection system”). The system includes a light source configured toilluminate at least a portion of the container; an image detectorconfigured to obtain an image of the liquid beneficial agent in theilluminated portion of the container; and a data processor coupled tothe image detector and programmed to analyze image data representing theimage from the image detector to obtain a particle concentration,measure a total image intensity value of the image data, and determine aquality level of the liquid beneficial agent using the data processorbased on the particle concentration and the measured total imageintensity value.

For purpose of illustration and not limitation, FIG. 13 is a diagramschematically depicting an exemplary detection system 200 for use withthe detection method described herein. An exemplary container 206 isshown, embodied as a pre-filled syringe, however the container can beany suitable container 206 for containing a liquid beneficial agent,including but not limited to a glass vial, quartz cell, or any othercontainer suitable for optical spectroscopy applications. An exemplarylight 204 is shown, embodied as a laser beam. However, the light 204 canbe any suitable light for selectively illuminating at least a portion ofthe container, including but not limited to a standard light bulb and afluorescent lamp. For example and not limitation, a light source used toproduce light 204 in an exemplary detection system 200 is LaserMax® 647nm diode laser. An exemplary image detector 202 is shown, embodied as aCCD camera and lens, however the image detector 202 can be any suitableimage detector for obtaining an image and providing image data. Forexample and not limitation, an image detector 202 used in an exemplarydetection system 200 is an Optronics® QPX-285C Digital Microscope Camerawith an Olympus® 10× objective lens. Exemplary optical elements 208 areshown, embodied as cylindrical lenses, however the optical elements 208are optional and can correspond to the shape of container 206 to permitthe capture of an undistorted image. For example and not limitation,exemplary optical elements 208 used to focus the image detector 202 andlight 204 in an exemplary detection system 200 are Edmund Optics®cylinder lenses having a focal length of 50 nm. An exemplary processor601 is shown, which is embodied as a component of the computer systemarchitecture 600, as shown in FIG. 14. For example and not limitation,an exemplary processor 601 is an Intel Pentium 4®.

As an example and not by limitation, as shown in FIG. 14, the computersystem having architecture 600 can provide functionality as a result ofprocessor(s) 601 executing software embodied in one or more tangible,computer-readable media, such as memory 603. The software implementingvarious embodiments of the present disclosure can be stored in memory603 and executed by processor(s) 601. A computer-readable medium caninclude one or more memory devices, according to particular needs.Memory 603 can read the software from one or more othercomputer-readable media, such as mass storage device(s) 635 or from oneor more other sources via communication interface. The software cancause processor(s) 601 to execute particular processes or particularparts of particular processes described herein, including defining datastructures stored in memory 603 and modifying such data structuresaccording to the processes defined by the software. An exemplary inputdevice 633 can be, for example, the imaging device 202 coupled to theinput interface 623 to provide image data to the processor 601. Anexemplary output device 634 can be, for example, an indicator 210, suchas an LED light, coupled to the output interface 623 to allow theprocessor 601 to provide an indication to the user that a beneficialagent sample is acceptable or unacceptable. Additionally oralternatively, the computer system 600 can provide an indication to theuser by sending text or graphical data to a display 632 coupled to avideo interface 622. Furthermore, any of the above components canprovide data to or receive data from the processor 601 via a computernetwork 630 coupled the network interface 620 of the computer system600. In addition or as an alternative, the computer system can providefunctionality as a result of logic hardwired or otherwise embodied in acircuit, which can operate in place of or together with software toexecute particular processes or particular parts of particular processesdescribed herein. Reference to software can encompass logic, and viceversa, where appropriate. Reference to a computer-readable media canencompass a circuit (such as an integrated circuit (IC)) storingsoftware for execution, a circuit embodying logic for execution, orboth, where appropriate. The present disclosure encompasses any suitablecombination of hardware and software.

The systems and methods provided herein can be utilized to inspect avariety of liquid beneficial agents, including but not limited to smallmolecule pharmaceuticals and large molecule biologics. For example,proteins having a protein concentration between about 0.1 mg/ml andabout 200 mg/ml can be inspected. Proteins inspected using the systemsand methods provided herein can be, including but not limited to, fusionproteins, antibodies, and any other suitable proteins. An exemplaryantibody inspected using the systems and methods provided herein is ananti-Tumor Necrosis Factor alpha (TNFα) antibody, or antigen-bindingfragment thereof.

The systems and methods provided herein can be utilized to ensure that abeneficial agent product has a predetermined quality level. The qualitylevel can be related to the amount and/or size of aggregates,contaminants, or other particles in the beneficial agent. By using themethod and system disclosed herein, this determination can be made atthe time and site of manufacture, packaging, or even shipment.Additionally, or alternatively, individual inspections can be performedby the pharmacist, physician, and/or use if a suitable beneficialtreatment product is available in accordance with the disclosed subjectmatter. Such a beneficial treatment product includes a containercontaining a liquid beneficial agent; a light source configured toilluminate at least a portion of the container; an image detectorconfigured to obtain an image of the liquid beneficial agent in theilluminated portion of the container; and a data processor coupled tothe image detector. The data processor is programmed to analyze imagedata representing the image from the image detector to obtain a particleconcentration, measure a total image intensity value of the image data,and determine a quality level of the liquid beneficial agent using thedata processor based on the particle concentration and the measuredtotal image intensity value.

While the disclosed subject matter is described herein in terms ofcertain preferred embodiments, those skilled in the art will recognizethat various modifications and improvements can be made to the disclosedsubject matter without departing from the scope thereof. Moreover,although individual features of one embodiment of the disclosed subjectmatter can be discussed herein or shown in the drawings of the oneembodiment and not in other embodiments, it should be apparent thatindividual features of one embodiment can be combined with one or morefeatures of another embodiment or features from a plurality ofembodiments.

In addition to the specific embodiments claimed below, the disclosedsubject matter is also directed to other embodiments having any otherpossible combination of the dependent features claimed below and thosedisclosed above. As such, the particular features presented in thedependent claims and disclosed above can be combined with each other inother manners within the scope of the disclosed subject matter such thatthe disclosed subject matter should be recognized as also specificallydirected to other embodiments having any other possible combinations.Thus, the foregoing description of specific embodiments of the disclosedsubject matter has been presented for purposes of illustration anddescription. It is not intended to be exhaustive or to limit thedisclosed subject matter to those embodiments disclosed.

It will be apparent to those skilled in the art that variousmodifications and variations can be made in the method and system of thedisclosed subject matter without departing from the spirit or scope ofthe disclosed subject matter. Thus, it is intended that the disclosedsubject matter include modifications and variations that are within thescope of the appended claims and their equivalents.

We claim:
 1. A method for detection of particles in a liquid beneficialagent contained within a container, comprising: selectively illuminatingat least a portion of the liquid beneficial agent; obtaining an imagefrom the illuminated portion of the liquid beneficial agent; analyzingimage data representing the image, using a data processor, to obtain aparticle concentration; measuring an image intensity value of the imagedata using the data processor; and determining a quality level of theliquid beneficial agent using the data processor based on the particleconcentration and the measured image intensity value.
 2. The methodaccording to claim 1, wherein selectively illuminating the portion ofthe liquid beneficial agent comprises focusing light through an opticalelement corresponding to the container to provide an undistorted imageof the liquid beneficial agent.
 3. The method according to claim 1,wherein selectively illuminating the portion of the liquid beneficialagent comprises forming a thin sheet of illumination in the illuminatedportion of the liquid beneficial agent.
 4. The method according to claim1, wherein the liquid beneficial agent is selectively illuminated withlight having a wavelength in a range from about 200 nm to about 1100 nm.5. The method according to claim 1, wherein the image is obtained bylight scattering from particles in the illuminated portion of the liquidbeneficial agent.
 6. The method according to claim 1, wherein the liquidbeneficial agent has intrinsic fluorescence and the beneficial agent isselectively illuminated with light having an excitation wavelengthsuitable to cause the liquid beneficial agent to emit fluorescent lightof an emission wavelength.
 7. The method according to claim 6, whereinobtaining the image comprises using an optical filter corresponding tothe emission wavelength of the emitted fluorescent light.
 8. The methodaccording to claim 1, wherein obtaining the image comprises focusing theimage at an image detector through an optical element corresponding tothe container to provide an undistorted image from the liquid beneficialagent.
 9. The method according to claim 1, wherein obtaining the imagecomprises: capturing a first image and a second image from theilluminated portion of the liquid beneficial agent; and using differenceimage analysis on the first image and the second image to obtain theimage.
 10. The method according to claim 1, further comprisingcalibrating an image detector to a predetermined sensitivity.
 11. Themethod according to claim 1, wherein analyzing the image data to obtaina particle concentration threshold is performed using a single imageframe.
 12. The method of claim 1, wherein obtaining the particleconcentration comprises counting a number of particles exceeding a sizethreshold to generate a particle size distribution.
 13. The method ofclaim 12, wherein counting a number of particles exceeding a sizethreshold comprises measuring particle scattering intensities toestimate the particle size distribution.
 14. The method according toclaim 1, wherein measuring the image intensity value of the image datacomprises: determining a pixel intensity value of each pixel of aplurality of pixels of the image data using the data processor; andcombining the pixel intensity values of the plurality of pixels todetermine the image intensity value using the data processor.
 15. Themethod according to claim 1, wherein determining the quality of theliquid beneficial agent comprises comparing the particle concentrationto a particle concentration threshold.
 16. The method according to claim15, wherein determining the quality of the liquid beneficial agentfurther comprises comparing the image intensity value to an imageintensity threshold.
 17. The method according to claim 16, wherein theparticle concentration threshold and the image intensity threshold areobtained from a representative profile.
 18. The method according toclaim 1, further comprising determining an average molecular mass of theparticles using the image intensity value, wherein the quality level isfurther determined using the average molecular mass.
 19. The methodaccording to claim 1, further comprising providing an indication to auser that the liquid beneficial agent is unsuitable if the quality leveldoes not exceed a predetermined quality level.
 20. The method accordingto claim 1, wherein the detection is performed on a plurality ofcontainers in a high-throughput manner.
 21. A system for detection ofparticles in a liquid beneficial agent within a container, comprising: alight source configured to illuminate at least a portion of the liquidbeneficial agent; an image detector configured to obtain an image fromthe illuminated portion of the liquid beneficial agent; and a dataprocessor coupled to the image detector and programmed to: analyze imagedata representing the image from the image detector to obtain a particleconcentration, measure an image intensity value of the image data, anddetermine a quality level of the liquid beneficial agent using the dataprocessor based on the particle concentration and the measured imageintensity value.
 22. A beneficial treatment product, comprising: acontainer containing a liquid beneficial agent; a light sourceconfigured to illuminate at least a portion of the liquid beneficialagent; an image detector configured to obtain an image from theilluminated portion of the liquid beneficial agent; and a data processorcoupled to the image detector and programmed to: analyze image datarepresenting the image from the image detector to obtain a particleconcentration, measure an image intensity value of the image data, anddetermine a quality level of the liquid beneficial agent using the dataprocessor based on the particle concentration and the measured imageintensity value.
 23. A liquid beneficial agent having a predeterminedquality level determined by a method comprising: selectivelyilluminating at least a portion of the liquid beneficial agent;obtaining an image from the illuminated portion of the liquid beneficialagent; analyzing image data representing the image, using a dataprocessor, to obtain a particle concentration; measuring an imageintensity value of the image data using the data processor; anddetermining a quality level of the liquid beneficial agent using thedata processor based on the particle concentration and the measuredimage intensity value.
 24. The liquid beneficial agent of claim 23,wherein the liquid beneficial agent comprises a small molecule.
 25. Theliquid beneficial agent of claim 23, wherein the liquid beneficial agentcomprises a protein.
 26. The liquid beneficial agent of claim 25,wherein the liquid beneficial agent has a protein concentration betweenabout 0.1 mg/ml and about 200 mg/ml.
 27. The liquid beneficial agent ofclaim 25, wherein the protein is a fusion protein.
 28. The liquidbeneficial agent of claim 25, wherein the protein is an antibody. 29.The liquid beneficial agent of claim 28, wherein the antibody is ananti-Tumor Necrosis Factor alpha (TNFα) antibody, or antigen-bindingfragment thereof.